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Thank you! I'd say pretty close. But S2 is not open source, and the OSS version (https://github.com/s2-streamstore/s2) is S2-Lite, which is single-node only and uses SlateDB.

SlateDB is great, but it's not purpose-built for streaming workloads. With PicoMQ, the goal is to really do one thing well. It would have been far easier to just extend SlateDB, but instead, the S3Stream engine is built from the ground up with AutoMQ's core primitives.

Not to mention, Pico supports multi-node/cluster deployments and a bunch of other features (no feature gating).

Indeed! The binary even embeds the admin dashboard. A good starting point to get the hang of PicoMQ: https://picomq.com/docs/playground

On the same boat, and honestly, it’s not getting the attention it deserves. Given Databricks acquired ElectricSQL primarily for PGlite, the Durable Streams project is likely going to be abandoned unless new maintainers step in.

I did, in fact, initially write PicoMQ with OpenRaft, similar to Ursala, but I really wanted the operational complexity to be minimal and the nodes to be stateless (at least for most use cases), Pico uses SQL database as a metadata command log, inspired by RisingWave.

But Ursala would, without a doubt, have better durability ACK latency, as it wouldn’t have to wait for an ACK from S3. That said, I do plan on extending disk/EBS-staged WAL to hit similar low-latency durability ACK numbers. But again, most use cases don’t need single-digit-millisecond latency for ACKs.

I'm glad you asked, and yes, PicoMQ does have some Kafka-like semantics. However, Kafka is great at being a huge pipe, so you'd create topics like tables. PicoMQ, on the other hand, recommends creating granular streams that make the most sense, say, by user, session, or vehicle (still bottomless).

And it's also fair to question write performance, since it's backed by object storage. The optimization is primarily from the shared WAL across streams, server-side batching, and client-side in-memory pipelining, especially with HTTP/2, without as much connection pool overhead.

In practice, you can go to the extent of achieving up to 100 MiB/s throughput per stream. Considering how granular streams can be, you'd rarely need as much. The latency for a durability ACK is, however, the price to pay, which is going to be ~250 ms, or lower with S3 Express, which I'd say covers most real-time use-cases. The design itself is easy enough to extend to a disk-staged WAL for single-digit durability ACK latency.

Not familiar with this particular library, but similar libraries use S3 Express One Zone which has write latency <10ms, so you can use that for the WAL and compaction can move data onto other storage classes in the background.

Regular S3 has write latency 100-150ms, which might be fine depending on your workload anyway.

Thank you! I spent a decent chunk of time designing PicoMQ, so the documentation had a natural progression.

Exactly, streams can essentially be rooms, and since the ordering is preserved, a Discord-like application is a strong use case. I’m even considering building one using PicoMQ as an example showcase.

The pricing is going to be dirt cheap, and the best part is how easy it is to scale up vertically or add nodes. For some raw numbers, assuming 1M messages/day, 200B per message, ~6GB/month, all-inclusive, it would be $30 to $150 a month, and storage would be the cheapest part.